Two-Stage Optimization of Battery Energy Storage Capacity to Decrease Wind Power Curtailment in Grid-Connected Wind Farms

Abstract

As wind power makes an increasing contribution to power systems, the problems associated with wind power curtailment have become a concern in recent years. Battery energy storage (BES) can reduce the effects of wind power curtailment by peak shaving and wind power forecast error compensation. Accordingly, the operational constraints of power systems and wind power uncertainty should be considered in the optimization of BES capacity installed at wind farms. This paper proposes a two-stage method to determine the optimal power and capacity of BES in systems including thermal plants, wind farms, and BES. In the first stage, the unit commitment of thermal generators and scheduled wind farm output are optimized with ac power flow constraints modeled by second-order cone programming. Time series of the wind farm output generated by Monte Carlo simulations are used for BES optimization. In the second stage, operational strategies for BES are designed. The simulation results indicate that cooperation between the BES and wind farm using the proposed method can reduce the costs of both wind farms and thermal plants. Finally, a sensitivity analysis is performed to assess the influence of the BES unit cost and wind power penetration on the optimal power and capacity of BES.